Jun 08, 2015

TM Forum Live: Big Data and KISS

By Jose Diaz


Jose's blog first appeared in Wireless Week.

We've heard it time and time again: Keep it Simple Stupid (KISS). And now, after attending TM Forum this week, it looks like this applies to Big Data strategies too.

Many of our discussions surrounded Big Data, but above all else, the hot topic at this year's event was the need for a radical simplification of systems and processes that meet the business needs of today, while preparing for the future.

Long gone are the days when the most effective strategies that emerged from the operators' IT departments loaded up on new platforms, systems and "critical" functionality that were often underutilized, or even worst yet, not fully deployed. Essentially, through this stockpile of technology, we all have contributed to what I call, "Telco Diogenes Syndrome."

To overcome this "syndrome", operators need to focus on making their infrastructures "lean and mean" to develop a digital ecosystem that can manage Big Data as well as The Internet of Things (IoT), Network Functions Virtualization (NFV) and Software Defined Networking (SDN)—and be ready for innovative technologies on the horizon. After hearing about all the legacy systems that are still managing major functions in businesses, this is no easy task.

Big Data: Challenges and Opportunities

Attendees couldn´t walk three steps at the show without bumping into operators, most of them key decision makers, with whom the subject of the conversation was Big Data. The discussions focused more on what to do with it and how to deploy the processes that will allow operators to squeeze out the "ambrosia" from their vast amount of data.

We all agreed, the volume and variety of data that is being passed through networks is staggering. Big Data is growing at an exponential rate, and companies will need to prepare themselves at a rate just as fast, if not faster. It's no longer just data, it's also the analysis of the data which is critical as well as how to monetize it. It's definitely full of challenges, but with more opportunities to make data profitable.

BIGGEST CHALLENGES: Business, Technology & Regulatory

We've found that Big Data's biggest challenges can be divided into three silos: business, technology and regulatory.


Business Challenges

We need to focus on business analytics, accurate forecasting, adopting new tools and technologies, and getting real-time insights. One of the biggest questions we discussed was how can we monetize Big Data? How can we gain profit from something that seems to be costing us time, money and resources to keep up with?

  • Business analytics: Businesses need to be able to use analytics to increase their operational intelligence. Is what we are doing working? Who is it working for?
  • Accurate forecasting: Using these analytics to make reliable inferences about the future of the market. We know what we did, so how can we do it better? What's next for our demographic? What can we infer that our demographic will respond to?

Real-time insights are the key to making sure that the analytics and forecasting are worth it. Time is essential. Companies want to know what's going on immediately so they can figure out how to respond accordingly. Big Data can do this.

Technology Challenges

Simplify, simplify, simplify! Agile IT is the business and simplification is the key. Much of the event and extensive primary research in this area over the last 18 months can be summed up: From an architectural point of view, the fewer systems you have, the more agile you will be.

Some key areas of focus:

  • By combining legacy systems with modern systems, companies can reduce cost. Evolution, not revolution is the fundamental here.
  • Prepare the infrastructure for business-critical production applications.
  • The customer experience depends on high availability.
  • Data must be analyzed for predictive analytics and targeted marketing campaigns.
  • Don't forget hardware, network and data management applications
  • Data storage must have the capacity to hold and update data at a low cost
  • The network must be able to efficiently transfer data to/from frameworks and architectures, while providing for future growth
  • Data management applications must be flexible for processing, organizing and utilizing massive amounts of data in real time

Regulatory Challenges

We need to be aware of existing and new regulations that restrict the use, storage and collection of certain types of data. Will Europe be the next to make up its mind on net neutrality?

Across these three silos, there must be collaboration to overcome these challenges. For example, the business and technology silos need to work together to find synergies and automate IT and business processes for the most efficient and effective operation across the enterprise. Work together as a team Less is more.

Endless Opportunities: More Revenue

Despite all the challenges, there are many opportunities for operators to monetize on Big Data. These include:

  • Increasing Revenue: Big Data allows you to tailor ad campaigns and offerings to the consumer's needs. Information can be obtained in real time, and future insights on market trends can be decided through predictive analytics.
  • Decreasing Costs: For fraud prevention, companies can track activity patterns by programming computers to look for known red flags. By looking for fraud through tracking, companies can move from a reactive to proactive approach. Rather than waiting for fraud to happen, Big Data analytics can shut it down and fix the issue before damaging problems occur. An optimized and automated network can also cut costs by reducing OpEx enhance allocation of resources.
  • Improving the customer experience: With all the competition, customer experience needs to be a differentiation factor in this saturated market. Big Data can help companies provide tailored products and services based on targeted and predictive marketing. Instant customer feedback can help company's sales and marketing initiatives on the right track and reduce churn—keeping existing customers happy while adding new ones.

Key Takeaways from TMForum for Big Data Strategies

Operators need to take the time to build a short-term and a long-term strategy:

For the short term, construct an initial assessment in terms of challenges in business, technology and regulatory. For your long-term strategy, it's important to:

  • Build a business strategy that can increase your revenue through improving both your customer experience as well as improving Capex and Opex.
  • Build a technology strategy that focuses on updating hardware, optimizing your network and ensuring your data management applications can do the job—sort, store and analyze the zettabytes of data flowing through your servers.
  • Keep up with regulations and build them into your plans.
  • Make sure the business strategy and technology strategy are in alignment.

The Big Data train has left the station and is moving full steam ahead. It's gaining speed so rapidly that it's time for everyone to be on board. Industry analysts predict that global data traffic will be 100 trillion GB by 2025. Are you ready?

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Jose Diaz is EMEA VP Business Development at Excelacom; he is responsible for the EMEA strategy, planning and execution of all aspects of Excelacom’s sales efforts.

More about Jose

Innovation meets performance.